Vendor-Centric Data Model Architecture for Database Consistency
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Solution Overview
Problem
Current data models for tracking work done by vendors for clients, such as client-centric and client-commingled models, face issues like redundancy, inconsistency, security vulnerabilities, and scalability problems, leading to inefficiencies and potential data breaches.
Innovation Solution
A vendor-centric data model is introduced, where vendor information is stored separately in a vendor directory, allowing for centralized management and automatic updates across client databases, ensuring consistency and security, and enabling efficient vendor management and client access control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a client-centric data model is used, then each client can have separate control over their vendor information, but redundant data entry occurs and inconsistencies arise between different client databases
Solution Approach 1:
The system segments vendor information into two distinct layers: a global vendor master database that stores unique vendor records, and client-specific instances that reference these global records. This segmentation allows vendor information to be maintained centrally while enabling client-specific customization without redundancy.
Solution Approach 2:
The vendor master database acts as an intermediary layer between the service provider and multiple clients. Instead of direct connections between each client and the vendor information, all clients connect through the centralized vendor master, which mediates data access and ensures consistency across all client instances.
2Productivity
If a client-commingled data model is used, then vendor information can be shared across clients, but security vulnerabilities arise and processing speed degrades
Solution Approach 1:
The system segments the database architecture into separate client instances with isolated access controls, while maintaining a shared vendor master database. This segmentation allows efficient data sharing for vendor information while preserving security boundaries for client-specific data, preventing unauthorized access and maintaining processing speed.
Solution Approach 2:
Different parts of the system have different access permissions and data visibility. The vendor master database is accessible to all clients with appropriate permissions, while client-specific project data remains locally restricted. This local quality approach optimizes both security and processing efficiency by allowing selective data sharing.
3Reliability
If a client-centric data model is used, then client-specific data control is maintained, but vendor information becomes outdated across multiple client databases
Solution Approach 1:
The vendor master database serves as a central intermediary that automatically synchronizes vendor information to all client instances. When vendor information is updated in the master database, the changes are propagated to all connected clients, ensuring data accuracy without requiring complex manual synchronization across multiple client databases.
Solution Approach 2:
The system implements automatic data propagation mechanisms where the vendor master database self-updates client instances with any changes. This self-service approach eliminates the need for manual data entry and synchronization by each client, maintaining data accuracy automatically while reducing the complexity of data management.
Data Source
AI summary
A data network storing data relating to work done by vendors for clients is described. The network includes two or more servers, each server containing (1) an exhaustive vendor data base that contains client-independent vendor data for every vendor, and (2) one or more individual client databases, each containing client information for a single client. The exhaustive vendor data base is replicated between the servers, and the client information for each client is contained by one individual client data base on one server.